# snap-research/articulated-animation

Code for Motion Representations for Articulated Animation paper

Repository: https://github.com/snap-research/articulated-animation
Canonical: https://ross.abutalabs.com/products/articulated-animation
Homepage: https://snap-research.github.io/articulated-animation/
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: image-animation, video-generation, first-order-motion-model, deep-learning
Last push: 2025-06-01T00:59:56+00:00

## Health v2 (maintenance only)
Score: 43/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 24, release rhythm 35, longevity 100
- inputs: {"age_days": 1989, "days_push": 459, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1277, forks 349 (observed 2026-08-28T04:04:13.297377+00:00)

## What it is
Official research code for the CVPR 2021 paper 'Motion Representations for Articulated Animation' by Snap Research. It animates a static source image using motion extracted from a driving video by identifying and tracking articulated object parts in an unsupervised manner.

## Use cases
- animate a photo using motion from a driving video
- face reenactment from a video
- transfer pose from video to a still image
- train an image animation model on my own dataset
- compare against first-order motion model baselines
- generate talking head videos from a single image

## When to choose
- you need state-of-the-art articulated image animation with region-based motion representations
- you want pre-trained checkpoints and a quick Colab demo
- you are reproducing or building on CVPR 2021 animation research

## When to avoid
- you need a production-ready, supported product with a stable API
- you want real-time animation on CPU or mobile devices
- you need a maintained library with active feature development

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, image-processing, video-processing, machine-learning
- domain: computer-vision, deep-learning, machine-learning, image-processing
- platform: python, cross-platform
- tags: image-animation, motion-representation, first-order-motion-model, face-reenactment, pose-transfer, cvpr-2021, research-code, pytorch, video, gpu, linux

## Member repositories
- snap-research/articulated-animation (main) score 43

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:13.297377+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:02:51.902310+00:00, confidence not recorded.
  - readme: https://github.com/snap-research/articulated-animation (fetched 2026-08-28T04:04:13.297377+00:00, sha a9a2f8177aac)
  - homepage: https://snap-research.github.io/articulated-animation/ (fetched 2026-08-29T12:13:47.984595+00:00, sha 5a2dd865bf8e)
- Data as of 2026-08-30T08:39:29.467469+00:00.